1 citations · 2 across the 13 of their papers we have counts for
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Instrumental variables system identification with consistency
Simon Kuang, Xinfan Lin
Instrumental variables (eliminate the bias that afflicts least-squares identification of dynamical systems through noisy data, yet traditionally relies on external instruments that…
Assumed Density Filtering and Smoothing with Neural Network Surrogate Models
Simon Kuang, Xinfan Lin
The Kalman filter and Rauch-Tung-Striebel (RTS) smoother are optimal for state estimation in linear dynamic systems. With nonlinear systems, the challenge consists in how to propag…
Joint Parameterization of Hybrid Physics-Based and Machine Learning Li-Ion Battery Model
Jackson Fogelquist, Xinfan Lin
Electrochemical hybrid battery models have major potential to enable advanced physics-based control, diagnostic, and prognostic features for next-generation lithium-ion battery man…
Robust Estimation of Battery State of Health Using Reference Voltage Trajectory
Rui Huang, Jackson Fogelquist, Xinfan Lin
Accurate estimation of state of health (SOH) is critical for battery applications. Current model-based SOH estimation methods typically rely on low C-rate constant current tests to…
Debiasing Continuous-time Nonlinear Autoregressions
Simon Kuang, Xinfan Lin
We study how to identify a class of continuous-time nonlinear systems defined by an ordinary differential equation affine in the unknown parameter. We define a notion of asymptotic…